Generative AI (GenAI) is rapidly reshaping the financial services landscape, offering banks, insurers, and asset managers the promise of transformative gains in productivity, customer experience, and innovation. Yet, for all its potential, the journey to GenAI value is not a simple technology upgrade. Instead, it requires a systematic approach to overcoming five critical organizational 'debts': technology, data, process, skills, and culture. Only by addressing these foundational barriers can financial institutions unlock GenAI’s full potential and achieve sustainable, enterprise-wide impact.
Financial services organizations are often burdened by decades of legacy technology—complex, siloed systems built up through years of mergers, regulatory changes, and incremental upgrades. This technical debt slows innovation, increases costs, and makes integrating GenAI solutions challenging. GenAI, however, offers a unique opportunity: it can accelerate legacy modernization by automating code refactoring, streamlining integration, and enabling rapid prototyping of new digital services. Leading institutions are leveraging GenAI-powered platforms to read and rewrite legacy code, automate testing, and compress years of technical debt remediation into weeks. The key is to treat GenAI not as a bolt-on, but as a catalyst for re-architecting the technology stack for agility, scalability, and intelligence.
Data is the lifeblood of GenAI, but many financial institutions struggle with fragmented, poor-quality, or siloed data estates. Regulatory requirements, legacy systems, and organizational silos have led to inconsistent data governance and limited data accessibility. To realize GenAI’s promise—whether in risk modeling, customer personalization, or compliance automation—firms must invest in data modernization: cleansing, integrating, and governing data across the enterprise. This means breaking down silos, implementing robust data governance frameworks, and ensuring data quality and lineage. GenAI can assist by automating data mapping, anomaly detection, and even generating synthetic data for model training, but the foundation must be solid. Without high-quality, well-governed data, GenAI models are only as good as their weakest input.
Financial services are notorious for rigid, risk-averse processes—often justified by regulatory scrutiny but resulting in bureaucratic inertia. Process debt manifests as outdated workflows, manual handoffs, and slow decision cycles. GenAI’s true value emerges when organizations move beyond point solutions and use it to reimagine end-to-end processes: automating routine tasks, enabling real-time decisioning, and orchestrating complex workflows across front, middle, and back offices. The most successful institutions balance the discipline of the “navy” (compliance, governance) with the agility of the “pirate” (experimentation, rapid iteration). This means embedding GenAI into core processes while maintaining robust controls, and fostering a culture where innovation and compliance coexist.
The shift to GenAI is as much about people as it is about technology. Financial institutions face a dual challenge: a shortage of AI talent and a workforce unprepared for new ways of working. Skills debt arises when organizations fail to invest in upskilling, leaving employees unable to harness GenAI’s capabilities or adapt to new roles. Leading firms are addressing this by launching comprehensive training programs—blending technical, ethical, and strategic skills—and creating new roles such as AI product managers and model stewards. The goal is to move from a search for “AI talent” to cultivating an “AI mindset” across the organization, empowering employees to co-create with GenAI and drive continuous improvement.
Perhaps the most insidious barrier is culture debt: resistance to change, risk aversion, and a lack of alignment between business and technology. In financial services, where tradition and regulation run deep, culture debt can stall even the most promising GenAI initiatives. Overcoming it requires visible leadership commitment, clear communication of the GenAI vision, and incentives aligned to innovation and collaboration. It also means embedding responsible AI principles—transparency, explainability, and ethical use—into the organizational DNA, ensuring that GenAI adoption builds trust with regulators, customers, and employees alike.
Publicis Sapient is recognized as a market leader in Generative Enterprise Services, with deep expertise across the financial services value chain. Our integrated SPEED (Strategy, Product, Experience, Engineering, Data & AI) capabilities enable us to deliver end-to-end transformation—from advisory and platform development to implementation, change management, and continuous optimization. We partner with clients to:
The time to realize GenAI’s value in financial services is now—but only for those bold enough to tackle the five debts head-on. By systematically addressing technology, data, process, skills, and culture, financial institutions can move beyond pilots and proofs of concept to enterprise-wide transformation. The result? Sustainable productivity gains, enhanced customer experiences, new revenue streams, and a future-ready organization equipped to thrive in the age of generative AI.
Ready to unlock GenAI’s full potential? Publicis Sapient is your trusted partner for the journey ahead.